Summarization
Transformers
PyTorch
TensorBoard
Danish
mt5
text2text-generation
Generated from Trainer
Instructions to use RyeAI/DaMedSum-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RyeAI/DaMedSum-large with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="RyeAI/DaMedSum-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("RyeAI/DaMedSum-large") model = AutoModelForSeq2SeqLM.from_pretrained("RyeAI/DaMedSum-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
b71db0e
1
Parent(s): 45db536
Update README.md
Browse files
README.md
CHANGED
|
@@ -24,9 +24,11 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 24 |
|
| 25 |
## Model description
|
| 26 |
|
| 27 |
-
This repository contains a model for Danish abstractive summarisation of
|
| 28 |
|
| 29 |
-
This model is a fine-tuned version of
|
|
|
|
|
|
|
| 30 |
|
| 31 |
## Authors
|
| 32 |
Nicolaj Larsen,
|
|
|
|
| 24 |
|
| 25 |
## Model description
|
| 26 |
|
| 27 |
+
This repository contains a model for Danish abstractive summarisation of medical text.
|
| 28 |
|
| 29 |
+
This model is a fine-tuned version of DanSumT5-large trained on a danish medical text dataset.
|
| 30 |
+
|
| 31 |
+
The model was trained on 1 AMD MI250X GPU.
|
| 32 |
|
| 33 |
## Authors
|
| 34 |
Nicolaj Larsen,
|